ArticleOptics letters2015
Fast two-dimensional super-resolution image reconstruction algorithm for ultra-high emitter density.
Article in Optics letters, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Reconstruction of super-resolution STORM images using compressed sensing based on low-resolution raw images and interpolation.Biomedical optics express · 2017Article
- State space approach to single molecule localization in fluorescence microscopy.Biomedical optics express · 2017Article
- A state space based approach to localizing single molecules from multi-emitter images.Proceedings of SPIE--the International Society for Optical Engineering · 2017Article
- Roles of the novel coiled-coil protein Rng10 in septum formation during fission yeast cytokinesis.Molecular biology of the cell · 2016Article
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5 authors.
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Abstract
Single-molecule localization microscopy achieves sub-diffraction-limit resolution by localizing a sparse subset of stochastically activated emitters in each frame. Its temporal resolution is limited by the maximal emitter density that can be handled by the image reconstruction algorithms. Multiple algorithms have been developed to accurately locate the emitters even when they have significant overlaps. Currently, compressive-sensing-based algorithm (CSSTORM) achieves the highest emitter density. However, CSSTORM is extremely computationally expensive, which limits its practical application. Here, we develop a new algorithm (MempSTORM) based on two-dimensional spectrum analysis. With the same localization accuracy and recall rate, MempSTORM is 100 times faster than CSSTORM with ℓ(1)-homotopy. In addition, MempSTORM can be implemented on a GPU for parallelism, which can further increase its computational speed and make it possible for online super-resolution reconstruction of high-density emitters.
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